Towards spaces of harmonic functions with traces in square Campanato spaces and their scaling invariants
Bibliographic record
Abstract
For [Formula: see text] and [Formula: see text], let [Formula: see text] be the space of harmonic functions [Formula: see text] on the upper half-space [Formula: see text] satisfying [Formula: see text] and [Formula: see text] be the Campanato space on [Formula: see text]. We show that [Formula: see text] coincides with [Formula: see text] for all [Formula: see text], where the case [Formula: see text] was originally discovered by Fabes, Johnson and Neri [E. B. Fabes, R. L. Johnson and U. Neri, Spaces of harmonic functions representable by Poisson integrals of functions in BMO and [Formula: see text], Indiana Univ. Math. J. 25 (1976) 159–170] and yet the case [Formula: see text] was left open. Moreover, for the scaling invariant version of [Formula: see text], [Formula: see text], which comprises all harmonic functions [Formula: see text] on [Formula: see text] satisfying [Formula: see text] we show that [Formula: see text], where [Formula: see text] is the collection of all functions [Formula: see text] such that [Formula: see text] are in [Formula: see text]. Analogues for solutions to the heat equation are also established. As an application, we show that the spaces [Formula: see text] unify naturally [Formula: see text], [Formula: see text] and [Formula: see text] which can be effectively adapted and applicable to suit handling the well/ill-posedness of the incompressible Navier–Stokes system on [Formula: see text].
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".